按值排序 dataframe 返回“对于多索引，label 必须是一个元组，其中元素对应于每个级别。”

Question

Objective: Based off dataframe with 5 columns, return dataframe with 3 columns including one which is the count and sort by largest count to smallest.

What I have tried:

df = df[['Country', 'Year','NumInstances']].groupby(['Country', 'Year']).agg(['count'])

df = df.sort_values(by='NumInstances', ascending=False)

print(df)

Error: ValueError: The column label 'NumInstances' is not unique. For a multi-index, the label must be a tuple with elements corresponding to each level.

Before this gets mark as a duplicate, I have gone through all other suggested duplicates and it seems they all suggest using the same code as I have above.

Is there something small that I am doing that may be incorrect?

Thanks!

Answer 1

I guess you need to remove multi-index -

Try this -

df = df[['Country', 'Year','NumInstances']].groupby(['Country', 'Year']).agg(['count']).reset_index()

or -

df = df[['Country', 'Year','NumInstances']].groupby(['Country', 'Year'], as_index=False).agg(['count'])

Answer 2

Found the issue. Adding an agg to the NumInstances column made the NumInstances column name a tuple of ('NumInstances', 'sum'), therefore I just updated the sort code to:

df = df.sort_values(by=('NumInstances', 'sum'), ascending=False)